Senior Fraud Analyst

2 weeks ago

Old Toronto, Ontario, Canada Scotiabank Full time

The Role

As a key member of the Fraud Management Group in Canada, you will contribute to the overall success of the team by executing and delivering specific individual goals, plans, and initiatives in support of the team's business strategies and objectives. You will ensure that all activities conducted are in compliance with governing regulations, internal policies, and procedures.

Key Responsibilities

  • Develop and execute fraud strategies for customer onboarding and product applications.
  • Stay up-to-date with advanced analytics techniques and apply them to enhance fraud mitigation capabilities for multiple products across the Canadian Retail portfolio.
  • Report regularly on the performance of existing fraud strategies deployed in Canadian Banking.
  • Identify improvements to existing fraud strategies, procedures, and policies.
  • Maintain performance reporting and collaborate with business partners to assess trends that may impact the business.
  • Drive strong partnerships with Fraud Operations to identify opportunities for improvement, focusing on risk/return while ensuring alignment.
  • Identify and escalate fraud risks that exceed the Risk Appetite.
  • Leverage data mining tools (SAS, Python, R) to formulate fraud strategies that minimize fraud losses while maintaining a positive customer experience and controlling operating costs.
  • Lead/participate in the identification, development, and implementation of new initiatives.
  • Contribute to and support various projects and initiatives across the Fraud Management Group.
  • Understand how the Bank's risk appetite and risk culture should be considered in day-to-day activities and decisions.
  • Actively pursue effective and efficient operations of your respective areas, ensuring the adequacy, adherence to, and effectiveness of day-to-day business controls to meet obligations with respect to operational risk, regulatory compliance risk, AML/ATF risk, and conduct risk.
  • A University degree in statistics, mathematics, or computer science is required.
  • 3-5 years of analytical experience, preferably including statistical analysis, ideally related to Fraud Analytics or Risk Management.
  • Strong coding, organizing, and manipulating large amounts of data (SAS, R, Python) skills are essential.
  • Experience with PRM or similar fraud platforms is highly desirable.
  • Strong prioritizing, planning, analytical, presentation, project management, and relationship building skills are required.
  • Strong communication skills are essential for effective collaboration with clients, vendors, and management.

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